采用VR技术展示建筑节点结构的实践

Dihua Lv
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引用次数: 0

摘要

随着虚拟现实(简称VR)和人工智能技术的发展和成熟,全景VR漫游被越来越多的行业所应用。在建筑工程行业中,由于一些关键建筑节点结构复杂,应用全景VR漫游技术建模将起到显著降低设计、施工和管理人员工作量和理解难度的作用。因此,本研究将全景VR漫游中信念传播(BP)算法的视差地图生成方法改进为采用极限匹配的形式,并对其中的能量函数和匹配原语进行优化,提出了一种基于改进BP算法的全景VR漫游空间模型构建方法。实验结果表明,本文提出的全景VR漫游空间模型构建方法可以显著提高建筑节点图像的空间建模质量,在获得200次迭代次数时,基于改进信念传播(IBP)、GC、BP和DP算法设计的VR漫游空间模型结构相似度归一化值分别为3.32、3.23、2.96和2.84。也是比较方法中最高的,例如当样本数为400时,IBP方案的计算时间为14.73±0.85 min,其他三种方案的计算时间最高为6.86±0.67 min。因此,该虚拟空间建模方法更适合计算时效性要求较低的应用场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VR technology used to show the practice of architectural node structure
With the development and maturity of virtual reality (VR for short) and artificial intelligence technology, panoramic VR roaming is applied to more and more industries. In the construction engineering industry, due to the complex structure of some key building nodes, the application of panoramic VR roaming technology modeling will play a role in significantly reducing the workload and understanding difficulty of design, construction and management personnel. Therefore, this study improves the parallax map generation method of the belief propagation (BP) algorithm in the panoramic VR roaming to use the form of limit matching and optimizes the energy function and matching primitives in it, so as to propose a spatial model construction method of the panoramic VR roaming based on the improved BP algorithm. The experimental results show that the panoramic VR roaming space model construction method proposed in this study can significantly improve the quality of spatial modeling of building node images, and the normalized values of structural similarity of VR roaming space models designed based on Improved belief propagation (IBP), GC, BP, and DP algorithms are 3.32, 3.23, 2.96, and 2.84, respectively, when the number of iterations is obtained 200 times, is also the highest among the compared methods, for example, when the number of samples is 400, the calculation time of IBP scheme is 14.73 ± 0.85 min, and the highest time of other three schemes is 6.86 ± 0.67 min. Therefore, this virtual space modeling method is designed to be more suitable for application scenarios that require lower computational timeliness.
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